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Dispersed Computer-Generated Resource Allocation In
Small Cell Networks With Full Duplex Heterogeneous
Wireless Sensor Network
P.MEENA¹, M.DEVADAS²
¹Mtech in WMC, Dept of ECE, VCE, Warangal, Telangana,India
Email: [email protected]
²Assoc.Prof,Dept of ECE ,VCE ,Warangal , Telangana, India
Email :[email protected]
ABSTRACT:
Wireless network virtualization has attracted
splendid attentions from every academia and
employer. Another growing generation for
next technology wireless networks is in-
band complete duplex (FD)
communications. Due to its promising
fashionable primary universal overall
performance, FD conversation has been
considered as an powerful way to
accumulate self-backhauls for small cells. In
this paper, we introduce wi-fi virtualization
into small cell networks, and recommend a
virtualized small mobile network form with
FD self-backhauls. We formulate the digital
beneficial resource allocation hassle in
virtualized small cell networks with FD self-
backhauls as an optimization hassle. Since
the formulated hassle is a mixed
combinatorial and non-convex optimization
trouble, its computational complexity is
immoderate. Moreover, the centralized
scheme may furthermore be stricken by
signaling overhead, antique dynamics
statistics, and scalability problems. To
treatment it effectively, we divide the
genuine trouble into sub problems. For the
primary sub problem, we switch it to a
convex optimization hassle, after which
treatment it with the resource of an green
alternating path technique of multipliers
(ADMM)-based totally completely allotted
set of hints. The 2ndsubproblem is a convex
problem, which can be solved thru manner
of every infrastructure business enterprise
organization. Extensive simulations are
finished with special tool configurations to
expose the effectiveness of the proposed
scheme Research problems are to decorate
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an Intrusion Detection System (IDS) of a
clustered HWSN to boom its lifetime
operation and common overall performance
of the tool within the presence of and
malicious nodes. Also, to address the
strength consumption, benefit in reliability,
remove and safety with the reason to
maximize the existence of a clustered
HWSN at the same time as thrilling software
QoS necessities. The proposed research is a
quite scalable cluster-primarily based totally
completely hierarchical keep in mind control
protocol for wireless sensor networks
(WSNs) to correctly cope with unreliable or
malicious nodes. The proposed paintings
considers take into account attributes
derived from communication and social
networks to evaluate the overall receive as
actual with of a sensor node. System
describes a heterogeneous WSN comprising
a massive sort of sensor nodes with
appreciably particular social and outstanding
of provider (QoS) behaviors as a manner to
yield “ground truth” node recognition
through “weighted balloting” leveraging
statistics of take delivery of as actual
with/reputation of neighbor nodes. To show
the software of the hierarchical bear in mind
manipulate protocol, it can be exercise to
really be given as real with-based definitely
without a doubt sincerely truly intrusion
detection gadget. For consider-primarily
based totally really intrusion detection, there
exists an crucial gain as real with threshold
for minimizing fake positives and faux
negatives hazard. Furthermore, remember-
based intrusion detection outperforms
conventional anomaly-based certainly
intrusion detection techniques in each the
detection possibility and the faux fantastic
possibility. The proposed research
furthermore makes use of AOMDV routing
protocol which gives sturdy fault tolerance
in WSNs. The protocol is based totally
definitely totally on a state-of-the-art
multipath structures paradigm this is
described mainly for heterogeneous WSN.
The method leverages an a good buy tons
less steeply-priced growth within the
community lifetime and a better resilience
and fault tolerance.
INTRODCUTION:
Advances in wireless conversation and
miniature electronics have enabled the
development of small, low-rate, low-energy
sensor nodes (SNs) with sensing and verbal
exchange competencies. Thus, the issues of
Wireless Sensor Networks (WSNs) have
grown to be famous studies subjects. WSN
is infrastructure based Network, the mass
deployment of SNs is completed in WSN
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and network is usual. The primary function
of WSN is to gather and monitor the
associated data which about the unique
surroundings. The SNs discover the
encompassing surroundings or the given aim
and deliver the facts to the sink the usage of
wireless communiqué. The statistics is then
analyzed to find out the dominion of the
aim. However, due to the layout form of
WSN and their hardware, WSNs be by
means of many resource constraints,
together with low computation functionality,
confined reminiscence and restricted energy.
Because WSNs are composed with the aid
of numerous low-price and small devices
that are generally deploy to an open, remote
and unprotected place, they're liable to
numerous types of assaults. A prevention
mechanism is used to counteract well-
known attacks. However, prevention
mechanisms can't resist normal assaults.
Therefore, the attacks are required to be
detected. An Intrusion Detection System
(IDS) is used frequently to stumble on the
packets in a community, and decide whether
they may be malicious packet or attackers.
Additionally, IDS can help to increase the
prevention device via received natures of
attack. Many wireless sensor networks
(WSNs) are deployed in an unattended
environment wherein strength replenishment
is hard. Due to restricted assets, a WSN is
calls for to meet the software precise Qi’s
requirements together with reliability,
minimum put off and security, and
additionally reduce power consumption to
lengthen the device beneficial lifetime.
Recently, prior research efforts had been
made to expand community architectures
and sensor hardware on the way to
successfully installation WSNs for a
diffusion of applications. However, Due to a
large type of WSN software necessities, a
widespread-cause WSN design can't satisfy
the goals of all packages. Network
parameters which include sensing variety,
node density and transmission variety
should be carefully taken into consideration
in step with specific programs, at the
network format degree. In order to benefit
this, it's miles very vital to seize the
influences of various network parameters on
community performance with recognize to
utility specs. Intrusion detection (i.e., object
monitoring) in a WSN may be seemed as a
tracking gadget for detecting the intruder
this is invading the community location.
Thus, it's far critical to amplify the intrusion
detection machine (IDS) that is able to
dealing with more extensive malicious
attacks with energy conservation mechanism
to growth system lifetime. In a WSN, there
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are two ways for the detection of an
interloper: unmarried-sensing detection and
a couple of-sensing detection. The intruder
may be efficaciously detected by most
effective a single sensor, in the unmarried-
sensing detection. On the opportunity hand,
within the a couple of-sensing detection the
intruder can best be detected with the
resource of more than one sensor. In a few
programs; the sensed records provided thru a
single sensor might not be ok for spotting
the intruder, due to the reality single sensors
can most effective sense a portion of the
intruder. The intrusion detection may be
analyzed in step with the functionality of
sensors in terms of the transmission range
and sensing range. In a heterogeneous WSN
a few sensors have a large electricity to
gather an extended transmission variety and
big sensing variety. Recent studies [2], [3]
tested that using heterogeneous nodes can
enhance performance and prolong the
gadget lifetime. In the latter case, nodes with
advanced sources function CHs appearing
computationally in depth obligations at the
same time as inexpensive less capable SNs
are applied particularly for sensing the
surroundings. Thus, the heterogeneous WSN
will boom the detection opportunity for a
given intrusion detection gadget. It is
thought in the studies network that
clustering [4], is a powerful answer for
carrying out scalability, energy
conservation, and reliability. Therefore the
cluster based totally heterogeneous WSN
can similarly improves the overall
performance of the network. By abstracting
and sharing resources among special parties,
virtualization can extensively reduce the
value of system and control in networks [1].
With the high-quality increase in Wi-Fi site
visitors and issuer, it's far inevitable to make
bigger virtualization to Wi-Fi networks [2],
[3]. In wireless virtualization, bodily
wireless community infrastructure and
bodily radio assets are abstracted and sliced
into digital wireless sources, which may be
shared with the aid of multiple activities.
After virtualization, the Wi-Fi community
infrastructure owned.
LITERATURE REVIEW:
Over the past few years, many protocols
exploring the energy consumption and QoS
gain particularly in reliability in HWSNs
have been proposed. In [8], the optimal
communication range and communication
mode were derived to maximize the HWSN
lifetime. In, the authors devised intra-cluster
scheduling and inter-cluster multi-hop
routing schemes to maximize the network
lifetime. They considered a HWSN with CH
nodes having larger energy and processing
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capabilities than normal SNs in the network.
The solution is drawn as an optimization
problem to balance energy consumption
across all nodes within the network along
with their roles. In either work [8], [9], no
consideration was taken in to the account
about the existence of malicious nodes in the
network. Relative to [9] the proposed work
considers heterogeneous nodes with
different densities and capabilities.
However, the work also considers the
presence of malicious nodes and explores
the tradeoff in energy consumption and QoS
gain in both security and reliability to
maximize the system lifetime. In the context
of secure multipath routing for intrusion
tolerance, in [10] the authors considered a
multipath routing protocol to tolerate black
hole and selective forwarding attacks. The
basic idea is to use overhearing to avoid
sending packets to malicious nodes. In [11]
the authors considered a disjoint multipath
routing protocol to tolerate intrusion using
multiple disjoint paths in WSNs. The
research proposed work also uses multipath
routing to tolerate intrusion. However, the
work specifically focuses on the amount of
energy being consumed for intrusion
detection and also to reduced energy
consumption in multipath routing to tolerate
intrusion. Moreover, the work consider
intrusion detection to detect and evict
compromised nodes as well as the best rate
to invoke intrusion detection so that the
energy consumption is reduced considerably
along with security and reliability gain to
maximize the system lifetime. In, voting
based IDS approach given the tradeoff
between energy loss vs. security and
reliability gain due to employment of the
voting-based IDS with the goal to prolong
the system lifetime. In general there are two
approaches by which energy efficient IDS
can be implemented in WSNs. One
approach is applicable to flat WSNs where
an intermediate node provides a feedback
about the maliciousness and energy status of
its neighbor nodes to the sender node (e.g.,
the source or sink node) who can then utilize
the knowledge to route packets to avoid
nodes with unacceptable maliciousness or
energy status. Another approach the author
adopt in [1] is to use local host-based IDS
for energy conservation (with SNs
monitoring neighbor SNs and CHs
monitoring neighbor CHs only), coupled
with voting to cope with node collusion for
implementing IDS functions. Energy
efficiency is achieved by applying the
optimal detection interval to perform IDS
functions. The solution author considers the
optimal IDS detection interval that can best
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balance intrusion accuracy vs. energy
consumption due to intrusion detection
activities, so as to maximize the system
lifetime. Compared with existing works
cited above, the proposed research work
extends from [1] with considerations given
to explore more extensive malicious attacks,
security and reliability, and also investigate
intrusion detection and multipath routing
based tolerance protocols to react to these
attacks. In addition to this, the proposed
work also consider smart and insidious
attackers which can perform more targeted
attacks, capture certain nodes with high
probability, alternate between benign and
malicious behavior and concatenate with
other attackers to avoid intrusion detection.
Also to investigate the use of trust/reputation
management [12], [13] to strengthen
intrusion detection through “weighted
voting” leveraging knowledge of
trust/reputation of neighbor nodes. Using
weighted voting scheme in intrusion
detection system (IDS) would considerably
reduce the false positives (FPs) and false
negatives (FNs) ratio. For effective fault
tolerance ad hoc on-demand multipath
distance vector (AOMDV) [14] is used to
achieve reliability and QoS gain with
minimum energy consumption.
LITERATURE REVIEW:
“Software-Defined and Virtualized
Future Mobile and Wireless Networks: A
Survey” With the proliferation of mobile
demands and increasingly multifarious
services and applications, mobile Internet
has been an irreversible trend.
Unfortunately, the current mobile and
wireless network (MWN) faces a series of
pressing challenges caused by the inherent
design. In this paper, we extend two latest
and promising innovations of Internet,
software-defined networking and network
virtualization, to mobile and wireless
scenarios. We first describe the challenges
and expectations of MWN, and analyze the
opportunities provided by the software-
defined wireless network (SDWN) and
wireless network virtualization (WNV).
Then, this paper focuses on SDWN and
WNV by presenting the main ideas,
advantages, ongoing researches and key
technologies, and open issues respectively.
Moreover, we interpret that these two
technologies highly complement each other,
and further investigate efficient joint design
between them
“Wireless world 2020: Radio interface
challenges and technology enablers”
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Future pervasive communication system
requirements for two to three orders of
magnitude capacity improvement, flexible,
fast deployment, and cost/energy efficiency
are expected to revolutionize the way we
design and use wireless networks. From a
network infrastructure perspective, the
emphasis is placed on achieving ubiquitous,
real-time high data rate communications
“anytime-anywhere,” including at cell-edge,
through Small Cell Network architectures
and Heterogeneous Cellular Networks
(HetNets). From a pervasive systems’
perspective, the vision of the Internet of
Things suggests the integration between
ubiquitous computing and wireless
communications targeting a reliable
connectivity of things, i.e., computers,
sensors, and everyday objects equipped with
transceivers. From a backhaul bandwidth,
network resource sharing, and optimization
perspective, cloud-based processing and
radio access network virtualization provide a
revolutionary approach toward balancing the
degree of centralization of physical and
virtual resources management. In this article
we analyze these three trends, present key
technology enablers, and assess suitable
performance merits in an effort to set the
scene for the wireless evolution in the era
beyond 2020. Over the last decade, cellular
networks have evolved from providers of
ubiquitous coverage for voice-
communication services to access ports
available “anytime-anywhere” for high data
rate, Internet-based data services. A three-
order of magnitude increase in the supported
data rates has been achieved, from several
kb/s in second generation, (2G) general
packet radio service (GPRS) to tens of Mb/s
in the latest long-term evolution (LTE)
systems. Nevertheless, even these fourth-
generation (4G) data rates may soon prove
inadequate, since the need for mobile data
capacity is growing at an unprecedented
rate. Recent market studies conducted by
global organizations [1], wireless forums
[2], telecom companies [3], and operators
[4], indicate that mobile data traffic has
doubled every year. Projecting this demand
a decade ahead, we are faced with the
socalled 1000x data challenge or capacity
crunch
“Network virtualization and resource
description in software-defined wireless
networks” Future networks will be defined
by software. In contrast to a wired network,
the software defined wireless network
(SDWN) experiences more challenges due
to the fast-changing wireless channel
environment. This article focuses on the
state-of-the-art of SDWN architecture,
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including control plane virtualization
strategies and semantic ontology for
network resource description. In addition, a
novel SDWN architecture with resource
description function is proposed, along with
two ontologies for the resource description
of the latest wireless network. Future
research directions for SDWN, control
strategy design, and resource description are
also addressed. It is widely accepted that
future networks will be defined by software.
With an ever-increasing demand for
broadband communications, new challenges
for networks keep coming up, such as
intelligent and ubiquitous connectivity,
efficient and flexible allocation of resources,
etc. To meet these challenges, future
networks must support convergence over
traditionally separated network domains and
offer greater granularity and flexibility in
control and in data throughput. With the
core idea of separating the control and data
planes, software defined networking (SDN)
has been considered as one promising
approach to meet those challenges in the
future. SDN naturally virtualizes the
network architecture and isolates the
data/control traffic. The logically centralized
control plane, with the global knowledge of
the network state, is able to obtain, update,
and even predict the global information.
Thus, SDN can guide end users to select the
best accessing network, or even provide
them with services from multiple networks.
SDN can be treated as one paradigm, rather
than an ossified architecture, where one
central software program, the controller, is
employed to optimize and dictate the overall
network behavior [1]. SDN can naturally be
extended to versatile scenarios, such as
optical networks, mobile wireless networks,
data center networks, and cloud computing.
The design of wireless network architecture
is much more challenging as it must deal
with various physical restrictions caused by
the fast-changing nature of wireless
channels [2, 3]. In the fifth generation (5G)
wireless communications, by implementing
SDN in eNodeB, distributing control is
proven to have higher efficiency [3]. Server
virtualization of wireless networks is also
more challenging than that of wired
networks, as the former has to satisfy the
requirements of both coherency and
hardware isolation [1]. Furthermore, to
implement multiple control strategies at real
networks, a universal agreed description of
network resources is needed. However, to
the best of the authors’ knowledge, no such
effort has been reported for software defined
wireless networking (SDWN),. One possible
reason might be that the existing test-beds
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for SDWN are relatively small and simple,
thus there is no need to develop specialized
technologies for network resource
description. Nevertheless, considering the
heterogeneous networks that exist in the real
world, it is important to reach an agreement
on the format and schema to uniquely
represent the network resources for all
layers. Hence, the massive resources can be
possibly manipulated simultaneously with
high efficiency
SYSTEM MODEL:
In this section, we first describe the
virtualized small cell network architecture.
Then we present the FD self-backhauling
mechanism where the SBSs can transmit and
receive data on the same spectrum
simultaneously.
A. Virtualized Small Cell Network
Architecture
We present a virtualized small cell network
architecture with multiple InPs and multiple
MVNOs, as shown in Fig. 1. There are M
InPs offering wireless access services in a
certain geographical area. Each InP deploys
and manages a cellular network with one
MBS and several self-backhauled SBSs.
There are N MVNOs, which provide various
services to their subscribers through the
same substrate networks. Following the
general frameworks of wireless network
virtualization [5], [26], the virtualized small
cell network architecture consists of three
layers: the physical resource layer (PRL),
the control and management layer (CML),
and the MVNO layer. The PRL, including
base stations (BSs), spectrum, power and
backhauls from different InPs, is responsible
for providing available physical resources.
Moreover, the PRL also provides CML with
the interfaces needed to control resources.
The CML virtualizes the physical resources
from different InPs and enables the sharing
for MVNOs. Then, the CML manages and
allocates the virtual resources to different
MVNO users. The resource management
functions in CML are realized by a virtual
network controller and a virtual resource
manager (VRM). The virtual network
controller of MVNOs is responsible to
collect the resource consumption prices
negotiated with InPs, and the users’
information (e.g., payment information and
QoS requirements) from MVNOs, then
feedback the resource allocation results to
MVNOs for the purpose of finishing the
settlement between MVNOs and InPs. To
maximize the total utility of all MVNOs, the
VRM is responsible to dynamically allocate
the virtual resources from multiple InPs to
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different MVNO users. Through the
virtualization architecture above, each
MVNO can have a virtual network
composed of the substrate networks from
multiple InPs. Hence each user can get
services via different access points (either
MBSs or SBSs) from different InPs.
Fig: A virtualized small cell network
architecture
B. Small Cell Self-backhauling
Mechanism Based on Full Duplex
Communications
As shown in Fig. 2(a), SBSs are equipped
with FD hardware, which enables them to
backhaul data for themselves. In the
downlink (DL), a SBS can receive data from
the MBS, while simultaneously transmitting
to its users on the same frequency band. In
the uplink (UL), a SBS can receive data
from the users, , the SBS can effectively
backhaul itself, eliminating the need for a
separate backhaul solution and a separate
frequency band. Therefore, self-backhauling
can significantly reduce the cost and
complexity of rolling out small cell
networks. In order to distinguish DL from
UL in access and backhaul transmissions,
we call the relevant links as access UL,
access DL, , the backhaul DL and access UL
will suffer some self-interference from
access DL and backhaul UL, respectively.
Different from the FD relay mechanism in
[20], the spectrum can be reused by different
SBSs and the SBSs can allocate resource to
their users flexibly in our self-backhaul
scheme. Compared to DL, UL usually has
less traffic. If the transmission of DL is
satisfied, the transmission of UL will also be
satisfied. As a result, we focus on the
transmission of DL in this paper.
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Fig:A small cell self-backhauling
mechanism based on full duplex
communications.
DISTRIBUTED VIRTUAL RESOURCE
ALLOCATION ALGORITHMS
It can be observed that the considered
problem is combinatorial and non-
convexity. The combinatorial nature comes
from the integer constraint C2. The non-
convexity is caused by the objective
function and constraint C1. As a result, a
brute force approach can be used to obtain
the optimal virtual resource allocation
policy. However, such a method is
computationally infeasible for a large
system and does not provide useful system
design insight. To reduce the computational
complexity, firstly, we assume the spectrum
allocation indicator vector α is fixed, and
then we convert the original problem into a
convex problem by variable transformation
and perspective function theory to solve X,
Y and Z. Secondly, based on the obtained
results, we can prove that the problem is
convex problem about α, then it’s easy to get
the optimized α by some convex
optimization algorithms. Furthermore, we
come back to first step with the result of α to
get the new values of X, Y , and Z. By
iterations like this for a number of times, the
values of X, Y , Z and α will converge, Will
introduce how to solve α when X, Y and Z
are fixed. we describe the whole process of
solution and the convergence of the
proposed algorithms.
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SIMULATION RESULTS:
In this section, the effectiveness of our
proposed virtualized small cell networks
with FD self-backhauls and distributed
virtual resource allocation algorithm will be
demonstrated by computer simulations. In
the simulations, we consider a 1Km × 1Km
square area covered by two InPs and two
MVNOs. In each InPs, there are one macro
BS and four SBSs. Each MVNO owns some
subscribed users. The number of subscribed
users in each MVNO will be varied in
different simulation scenarios, and they are
randomly located in the whole area. The
available bandwidth of both of the two InPs
are 10 MHZ. The transmit power of the
macro BS and the transmit power of the SBS
are 46dBm and 20dBm, respectively. The
channel propagation model refers to [35].
The SBSs are randomly deployed in the
area. This deployment of BSs is based on
the consensus that the location of macro BS
is usually calculated by network planning
but the location of SBS (e.g., fem to cell)
may depend on the users.
Fig :The total utility of MVNOs
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Fig: The average utility of users
Fig: The total MVNO utility of different
residual self interference gain
CONCLUSION:
we investigated the virtual resource
allocation issues in small cell networks with
FD self-backhauls and virtualization. We
first introduced the idea of wireless network
virtualization into small cell networks, and
proposed a virtual resource management
architecture, where radio spectrum, time
slots, MBSs, and SBSs are virtualized as
virtual resources. After virtualization, users
can access to different InPs to get
performance gain. In addition, we proposed
to use FD communications for small cell
backhauls. Furthermore, we formulated the
virtual resource allocation problem as an
optimization problem by maximizing the
total utility of MVNOs. In order to solve it
efficiently, the virtual resource allocation
problem is decomposed into two sub
problems. In this process, we transferred the
first sub problem into a convex problem and
solved it by our proposed ADMM-based
distributed algorithm, which can reduce the
computation complexity and overhead. The
second sub problem can be solved by each
InPs easily because of its convexity and
incoherence among InPs. Simulation results
showed that the proposed virtualized small
cell networks with FD self-backhauls are
able to take the advantages of both wireless
network virtualization and FD self-
backhauls. MVNOs, InPs, and users could
benefit from it, and the average throughput
of the small cell networks can be improved
significantly. In addition, simulation results
also demonstrated the effectiveness and
good convergence performance of our
proposed distributed virtual resource
allocation
REFERENCES:
[1] N. M. K. Chowdhary and R. Boutaba,
“A survey of network virtualization,”
Computer Net., vol. 54, no. 5, pp. 862–876,
Apr. 2010.
[2] C. Liang and F. R. Yu, “Wireless
network virtualization: A survey, some
research issues and challenges,” IEEE
Pramana Research Journal
Volume 8, Issue 10, 2018
ISSN NO: 2249-2976
https://pramanaresearch.org/253
Common. Surveys Tutorials, vol. 17, no. 1,
pp. 358–380, First quarter 2015.
[3] C. Liang, F. R. Yu, and X. Zhang,
“Information-centric network function
virtualization over 5G mobile wireless
networks,” IEEE Network, vol. 29, no. 3,
pp. 68–74, May 2015.
[4] M. Hoffmann and M. Staufer, “Network
virtualization for future mobile networks:
General architecture and applications,” in
Proc. IEEE ICC Workshops, 2011, pp. 1–5.
[5] F. Fu and U. C. Kozat, “Stochastic game
for wireless network virtualization,”
IEEE/ACM Trans. Netw., vol. 21, no. 1, pp.
84–97, Feb. 2013.
[6] Y. Zaki, L. Zhao, C. Goerg, and A.
Timm-Giel, “LTE mobile network
virtualization,” Mobile Networks and
Applications, vol. 16, no. 4, pp. 424–432,
Aug. 2011.
[7] G. Bhanage, D. Vete, I. Seskar, and D.
Raychaudhuri, “SplitAP: Leveraging
wireless network virtualization for flexible
sharing of WLANs,” in Proc. IEEE
Globecom, Dec. 2010, pp. 1–6.
[8] A. Banchs, P. Serrano, P. Patras, and M.
Natkaniec, “Providing throughput and
fairness guarantees in virtualized WLANs
through control theory,” Mobile Networks
and Applications, vol. 17, no. 4, pp. 435–
446, Aug. 2012.
[9] R. Kokku, R. Mahindra, H. Zhang, and
S. Rangarajan, “NVS: A substrate for
virtualizing wireless resources in cellular
networks,” IEEE/ACM Trans. Netw., vol.
20, no. 5, pp. 1333–1346, Oct. 2012.
[10] A. Tzanakaki, M. P. Anastasopoulos,
G. S. Zervas, and B. R. Rofoee,
“Virtualization of heterogeneous wireless-
optical network and IT infrastructures to
support cloud and mobile cloud services,”
IEEE Comm. Mag., vol. 51, no. 8, pp. 155–
161, Aug. 2013.
[11] H. Zhang, C. Jiang, N. Beaulieu, X.
Chu, X. Wang, and T. Quek, “Resource
allocation for cognitive small cell networks:
A cooperative bargaining game theoretic
approach,” IEEE Trans. Wireless Common.,
vol. 14, no. 6, pp. 3481–3493, June 2015.
[12] S. Bu and F. R. Yu, “Green cognitive
mobile networks with small cells for
multimedia communications in the smart
grid environment,” IEEE Trans. Veh. Tech.,
vol. 63, no. 5, pp. 2115–2126, June 2014.
[13] C. Ranaveera, P. Iannone, K.
Oikonomou, and K. Reichmann, “Design of
cost-optimal passive optical networks for
Pramana Research Journal
Volume 8, Issue 10, 2018
ISSN NO: 2249-2976
https://pramanaresearch.org/254
small cell backhaul using installed fibers,”
IEEE/OSA J. Opt. Common. &Netw., vol.
5, no. 10, pp. A230–A239, Oct. 2013.
[14] J. G. Andrews, H. Claussen, M. Dohler,
S. Rangan, and M. C. Reed, “Femtocells:
Past, present, and future,” IEEE J. Sel. Areas
Common., vol. 30, no. 3, pp. 497–508, Apr.
2012.
[15] W. Ni, I. Collings, X. Wang, and R. P.
Liu, “Multi-hop point-to-point FDD wireless
backhaul for mobile small cells,” IEEE
Wireless Comm., vol. 21, no. 4, pp. 88–96,
Aug. 2014.
[16] S. Hur, T. Kim, D. J. Love, R. J. V.
Krogmeier, T. A. Thomas, and A. Ghosh,
“Millimeter wave beam forming for wireless
backhaul and access in small cell networks,”
IEEE Trans. Common., vol. 61, no. 10, pp.
4391–4403, Oct. 2013.
.
Pramana Research Journal
Volume 8, Issue 10, 2018
ISSN NO: 2249-2976
https://pramanaresearch.org/255